A survey of machine learning algorithms and their applications in cognitive radio

Mustafa  Alshawaqfeh; Xu Wang; Ali Riza Ekti; Erchin Serpedin; Muhammad Zeeshan Shakir; Khalid Qaraqe

doi:10.1007/978-3-319-24540-9_66

A survey of machine learning algorithms and their applications in cognitive radio

Mustafa Alshawaqfeh
, Xu Wang
, Ali Riza Ekti
, Erchin Serpedin
, Muhammad Zeeshan Shakir
, Khalid Qaraqe

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Citations (Scopus)

Abstract

Cognitive radio (CR) technology is a promising candidate for next generation intelligent wireless networks. The cognitive engine plays the role of the brain for the CR and the learning engine is its core. In order to fully exploit the features of CRs, the learning engine should be improved. Therefore, in this study, we discuss several machine learning algorithms and their applications for CRs in terms of spectrum sensing, modulation classification and power allocation.

Original language	English
Title of host publication	Cognitive Radio Oriented Wireless Networks
Subtitle of host publication	10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers
Editors	Mark Weichold, Mounir Hamdi, Muhammad Zeeshan Shakir, Mohamed Abdallah, George K. Karagiannidis
Publisher	Springer Nature
Pages	790-801
Number of pages	12
Volume	156
ISBN (Electronic)	9783319245409
ISBN (Print)	9783319245393
DOIs	https://doi.org/10.1007/978-3-319-24540-9_66
Publication status	Published - 23 Apr 2015
Externally published	Yes
Event	10th International Conference on Cognitive Radio Oriented Wireless Networks - Hilton Hotel, Doha, Qatar Duration: 21 Apr 2015 → 23 Apr 2015 http://crowncom.org/2015/show/home

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Publisher	Springer
Volume	156
ISSN (Print)	1867-8211

Conference

Conference	10th International Conference on Cognitive Radio Oriented Wireless Networks
Abbreviated title	CrownCom'2015
Country/Territory	Qatar
City	Doha
Period	21/04/15 → 23/04/15
Internet address	http://crowncom.org/2015/show/home

Keywords

cognitive radio
machine learning
learning engine
spectrum sensing
modulation classification

Access to Document

10.1007/978-3-319-24540-9_66

Cite this

Alshawaqfeh, M., Wang, X., Ekti, A. R., Serpedin, E., Shakir, M. Z., & Qaraqe, K. (2015). A survey of machine learning algorithms and their applications in cognitive radio. In M. Weichold, M. Hamdi, M. Z. Shakir, M. Abdallah, & G. K. Karagiannidis (Eds.), Cognitive Radio Oriented Wireless Networks: 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers (Vol. 156, pp. 790-801). (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 156). Springer Nature. https://doi.org/10.1007/978-3-319-24540-9_66

Alshawaqfeh, Mustafa ; Wang, Xu ; Ekti, Ali Riza et al. / A survey of machine learning algorithms and their applications in cognitive radio. Cognitive Radio Oriented Wireless Networks: 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers. editor / Mark Weichold ; Mounir Hamdi ; Muhammad Zeeshan Shakir ; Mohamed Abdallah ; George K. Karagiannidis. Vol. 156 Springer Nature, 2015. pp. 790-801 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering).

@inproceedings{15910cb7177e44f0a58e58107df52b5d,

title = "A survey of machine learning algorithms and their applications in cognitive radio",

abstract = "Cognitive radio (CR) technology is a promising candidate for next generation intelligent wireless networks. The cognitive engine plays the role of the brain for the CR and the learning engine is its core. In order to fully exploit the features of CRs, the learning engine should be improved. Therefore, in this study, we discuss several machine learning algorithms and their applications for CRs in terms of spectrum sensing, modulation classification and power allocation.",

keywords = "cognitive radio, machine learning, learning engine, spectrum sensing, modulation classification",

author = "Mustafa Alshawaqfeh and Xu Wang and Ekti, \{Ali Riza\} and Erchin Serpedin and Shakir, \{Muhammad Zeeshan\} and Khalid Qaraqe",

year = "2015",

month = apr,

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doi = "10.1007/978-3-319-24540-9\_66",

language = "English",

isbn = "9783319245393",

volume = "156",

series = "Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering",

publisher = "Springer Nature",

pages = "790--801",

editor = "Mark Weichold and Mounir Hamdi and Shakir, \{Muhammad Zeeshan\} and Mohamed Abdallah and Karagiannidis, \{George K.\}",

booktitle = "Cognitive Radio Oriented Wireless Networks",

address = "Switzerland",

note = "10th International Conference on Cognitive Radio Oriented Wireless Networks, CrownCom'2015 ; Conference date: 21-04-2015 Through 23-04-2015",

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}

Alshawaqfeh, M, Wang, X, Ekti, AR, Serpedin, E, Shakir, MZ & Qaraqe, K 2015, A survey of machine learning algorithms and their applications in cognitive radio. in M Weichold, M Hamdi, MZ Shakir, M Abdallah & GK Karagiannidis (eds), Cognitive Radio Oriented Wireless Networks: 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers. vol. 156, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 156, Springer Nature, pp. 790-801, 10th International Conference on Cognitive Radio Oriented Wireless Networks, Doha, Qatar, 21/04/15. https://doi.org/10.1007/978-3-319-24540-9_66

A survey of machine learning algorithms and their applications in cognitive radio. / Alshawaqfeh, Mustafa ; Wang, Xu; Ekti, Ali Riza et al.
Cognitive Radio Oriented Wireless Networks: 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers. ed. / Mark Weichold; Mounir Hamdi; Muhammad Zeeshan Shakir; Mohamed Abdallah; George K. Karagiannidis. Vol. 156 Springer Nature, 2015. p. 790-801 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 156).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Qaraqe, Khalid

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AB - Cognitive radio (CR) technology is a promising candidate for next generation intelligent wireless networks. The cognitive engine plays the role of the brain for the CR and the learning engine is its core. In order to fully exploit the features of CRs, the learning engine should be improved. Therefore, in this study, we discuss several machine learning algorithms and their applications for CRs in terms of spectrum sensing, modulation classification and power allocation.

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Alshawaqfeh M, Wang X, Ekti AR, Serpedin E, Shakir MZ, Qaraqe K. A survey of machine learning algorithms and their applications in cognitive radio. In Weichold M, Hamdi M, Shakir MZ, Abdallah M, Karagiannidis GK, editors, Cognitive Radio Oriented Wireless Networks: 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21-23, 2015, Revised Selected papers. Vol. 156. Springer Nature. 2015. p. 790-801. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering). doi: 10.1007/978-3-319-24540-9_66

A survey of machine learning algorithms and their applications in cognitive radio

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Conference

Keywords

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